Complete AI TrainingYourJobSkills for your job

Skills / workflow

closed-loop-delivery

Use when a coding task must be completed against explicit acceptance criteria with minimal user re-intervention across implementation, review feedback, deployment, and runtime verification.

newProject & Program ManagementOperations & Supply ChainAI & Automation

Closed-Loop Delivery

Overview

Treat each task as incomplete until acceptance criteria are verified in evidence, not until code is merely changed.

Core rule: deliver against DoD (Definition of Done), not against code diff size.

When to Use

Use this skill when:

  • user gives a coding/fix task and expects end-to-end completion
  • task spans code + tests + PR comments + dev deploy + runtime checks
  • repeated manual prompts like "now test", "now deploy", "now re-check PR" should be avoided

Do not use this skill for:

  • pure Q&A/explanations
  • prod deploy requests without explicit human approval
  • tasks blocked by missing secrets/account access that cannot be inferred

Required Inputs

Before execution, define these once:

  • task goal
  • acceptance criteria (DoD)
  • target environment (dev by default)
  • max iteration rounds (default 2)

If acceptance criteria are missing, request them once. If user does not provide, propose a concrete default and proceed.

Issue Gate Dependency

Before execution, prefer using create-issue-gate.

  • If issue status is ready and execution gate is allowed, continue.
  • If issue status is draft, do not execute implementation/deploy/review loops.
  • Require user-provided, testable acceptance criteria before starting execution.

Default Workflow

  1. Define DoD
  • Convert request into testable criteria.
  • Example: chec

Subscribers only

The full skill, its 1 bundled files and every download is included with every paid Complete AI plan.

Details

Sourcecommunity
License
Risk labelsafe ("critical" means the skill may run commands or touch files — read before use)
FilesSKILL.md
Added2026-03-12

Related skills

acceptance-orchestrator

Use when a coding task should be driven end-to-end from issue intake through implementation, review, deployment, and acceptance verification with minimal human re-intervention.

address-github-comments

Use when you need to address review or issue comments on an open GitHub Pull Request using the gh CLI.

ai-loop

Runs a bounded spec-build-review development loop with explicit scope, stop conditions, and human approval gates for risky or ambiguous work.

airflow-dag-patterns

Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.

antigravity-workflows

Use when asked to ship a SaaS MVP, audit application security, build an AI agent, run browser QA, or design a domain model with multiple skills and verified checkpoints.

ask-questions-if-underspecified

Clarify requirements before implementing. Use when serious doubts arise.